Measuring visual pollution by outdoor advertisements in an urban street using intervisibilty analysis and public surveys
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Debates on the encroaching commercialization of public space by outdoor advertising highlight its possible negative impact on local quality of life and enjoyment of public spaces. These overstimulating outdoor advertisements are often considered a source of visual pollution, but cities have no standard way of measuring where it exists and its local impact, and thus cannot regulate it effectively. This study illustrates that visual pollution can be measured in a useful way by relating public opinion to the number of visible advertisements (intervisibility analysis). Using a 2.5D outdoor advertisement (OA) dataset (location and height) of a busy urban street in Lublin, Poland, this preliminary experiment translates visibility into visual pollution. It was found that streetscape views with more than seven visible OAs created visual pollution in this case study. The GIS-based methodology proposed could provide Lublin officials with a basic tool to assess and manage visual pollution, by informing permitting decisions on OAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it